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Off-channel water demand and consumption are critical components of water resource management, influenced by various natural and anthropogenic factors. This study systematically analysed these influencing factors and the methods for predicting off-channel water demand, aiming to provide insights for effective water resource planning and management at the catchment level. The research employed Cite Space for bibliometric analysis to identify current research trends, key hotspots, and systematically categorised the factors that influence the off-channel water demand, as well as the methods used for its prediction. Key factors affecting off-channel water demand in most catchments include population, water pricing, precipitation, and air temperature. Machine learning algorithms have emerged as a prominent tool for predicting off-channel water demand, often used alongside regression analysis to assess the influence of multiple factors. The quota index method remains widely applied in practical water resource management. Additionally, hybrid approaches, combining time series analysis with other methods, address limitations in standalone models and enhance prediction accuracy. Advances in remote sensing, geospatial big data, artificial intelligence, and machine learning algorithms have significantly improved the accuracy of off-channel water demand predictions, particularly at smaller scales. Future research should focus on enhancing the validation of prediction models and ensuring the robust integration of historical data to improve modeling reliability for off-channel water demand and consumption.

The most economically important trait of the Procambarus clarkii is meat quality. Protein deposition is essential in muscle growth and nutritional quality formation. The effects and potential mechanisms of feed protein sources on crustaceans' muscle protein deposition have not been elucidated. This study established an all-animal protein source (AP) and an all-plant protein source group (PP), with a feeding period of 8 weeks (four replicates per group, 45 individuals per replicate). The results demonstrated that muscle protein deposition, muscle fiber diameter, and hardness were significantly higher in the PP group (p < 0.05). The transcript levels of genes involved in protein synthesis were notably upregulated, while those of protein hydrolysis and negative regulators of myogenesis notably downregulated in PP group (p < 0.05). Furthermore, protein sources shaped differential intestinal microbiota composition and microbial metabolites profiles, as evidenced by a significant decrease in g_Bacteroides (p = 0.030), and a significant increase in taurochenodeoxycholic acid (TCDCA) in PP group (p = 0.027). A significant correlation was further established by Pearson correlation analysis between the g_Bacteroides, TCDCA, and genes involved in the MSTN-mediated protein deposition pathway (p < 0.05). In vitro anaerobic fermentation confirmed the ability of the two groups of intestinal flora to metabolically produce differential TCDCA (p = 0.038). Our results demonstrated that the 'Bacteroides-TCDCA-MSTN' axis may mediate the effects of different protein sources on muscle development and protein deposition in P. clarkii, which was anticipated to represent a novel target for the muscle quality modulation in crustaceans. [ABSTRACT FROM AUTHOR]

The study of dredged fill in Guangdong (GD), China, is of great significance for reclamation projects. Currently, there are relatively few studies on dredged fill in Guangdong, and there are many differences in the engineering characteristics of dredged fill foundations formed through land reclamation and natural foundations. In order to have a more comprehensive understanding of the physico-mechanical properties of blowing fill in the coastal area of GD and to understand the effect of its long-term creep row on the long-term settlement and deformation of buildings, the material properties, microstructure, elemental composition, triaxial shear properties, and triaxial creep properties of dredged fill in Guangdong were studied and analyzed through indoor geotechnical tests, scanning electron microscopy (SEM), X-ray diffraction (XRD), and conventional triaxial shear tests and triaxial creep tests. The test results showed that the Guangdong dredged fill is characterized by a high water content, high pore ratio, and high-liquid-limit clayey sand, and the mineral composition is dominated by quartz and whitmoreite. The scanning electron microscopy results showed that the particles of the dredged fill showed an agglomerated morphology, and the surface of the test soil samples had scaly fine flakes and a fragmented structure. In the triaxial shear test, the GD dredged fill showed strain hardening characteristics, and the effective stress path showed continuous loading characteristics; the consolidated undrained shear test showed that the GD dredged fill had shear expansion characteristics under low-perimeter-pressure conditions. It was found that, with an increase in bias stress, the axial strain in the consolidated undrained triaxial creep test under the same perimeter pressure conditions gradually exceeded the axial strain in the consolidated drained triaxial creep test. The results of this study are of theoretical and practical significance for further understanding the mechanical properties of silty soils in the region and for the rational selection of soil strength parameters in practical engineering design. [ABSTRACT FROM AUTHOR]

Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks. However, few studies focus on communities emerging between adjacent cities in big urban agglomerations, which we call "cross-city" communities. In this study, we introduce a novel framework to detect cross-city communities in urban agglomerations under different scales leveraging a large number of fine-grained mobile signaling data aiming to break the original administrative boundaries. Taking the Pearl River Delta (PRD) urban agglomeration in China as study area, we investigate the existence of potential communities at three scales, i.e. city-group level, city level and sub-city level. The partition results are expected to benefit transportation planning, urban zoning and administrative boundary re-delineation. The results from our study highlight the necessity of considering cross-city communities and their scale effects when examining urban spatial interactions. [ABSTRACT FROM AUTHOR]

The identification of Wheel/Rail Force (WRF) based on acceleration is a cheaper and convenient way to ensure safe operation. For this purpose, this paper describes an approach for the estimation of Vertical Wheel/Rail Force (VWRF) using dynamic signals from a track inspection train (TIT). Based on the vehicle dynamics theory, a VWRF estimation model is established, by which VWRF can be estimated with the measured vehicle acceleration. Rolling angle is a non-constant and hard-measured value which will affect estimation results. By deducing its relation with the difference between left and right track profiles, it can be got through the Vertical Axle Box Acceleration (VABA) and the length of the axle box. VWRF cannot be estimated only by filtering the Axle Box Acceleration (ABA). The mass participating in vibration (PVM) also has a great influence on it. With many tests and calculations, the relationship between the PVM and the wheelset mass is concluded, which made the estimation results much more accurate. The proposed method provides the basis for online high-precision estimate WRF and ensures safe operation. By comparing with a commercial WRF Inspection System, the railway application results identified that the proposed method can produce a satisfactory result. [ABSTRACT FROM AUTHOR]